code: def test_partial_decode_with_skip_decode(
      dummy_mnist: testing.DummyMnist,
  ):
      ds = dummy_mnist.as_dataset(
          split="train",
          decoders=decode.PartialDecoding(
              {
                  "image": features_lib.Image(shape=(None, None, 1)),
              },
              decoders={
                  "image": decode.SkipDecoding(),
              },
          ),
      )
      assert ds.element_spec == {
          "image": tf.TensorSpec(shape=(), dtype=tf.string)
      }
      for ex in ds.take(2):
          assert ex["image"].dtype == tf.string
  
file_path: datasets/tensorflow_datasets/core/decode/partial_decode_test.py
imports: import pytest
  import tensorflow
  from tensorflow_datasets import testing
  from tensorflow_datasets.core import decode
  from tensorflow_datasets.core import features
label_desc: Use image node_id 5 for calling a global function with example usage: test_partial_decode_with_skip_decode(dummy_mnist) without return types